Andrew Howard

41.1k total citations · 1 hit paper
16 papers, 1.0k citations indexed

About

Andrew Howard is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Andrew Howard has authored 16 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 2 papers in Computer Networks and Communications. Recurrent topics in Andrew Howard's work include Advanced Neural Network Applications (6 papers), Gaussian Processes and Bayesian Inference (5 papers) and Neural Networks and Applications (4 papers). Andrew Howard is often cited by papers focused on Advanced Neural Network Applications (6 papers), Gaussian Processes and Bayesian Inference (5 papers) and Neural Networks and Applications (4 papers). Andrew Howard collaborates with scholars based in United States, Denmark and United Kingdom. Andrew Howard's co-authors include Tony Jebara, Risi Kondor, Andrey Zhmoginov, Liang-Chieh Chen, Menglong Zhu, Mark Sandler, Yang Song, Serge Belongie, Yin Cui and Chen Sun and has published in prestigious journals such as Journal of Machine Learning Research, IEEE Transactions on Nuclear Science and arXiv (Cornell University).

In The Last Decade

Andrew Howard

15 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation

2018 386 citations Andrew Howard, Andrey Zhmoginov et al. arXiv (Cornell University) profile →

Peers

Countries citing papers authored by Andrew Howard

Since Specialization

Citations

This map shows the geographic impact of Andrew Howard's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew Howard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Howard more than expected).

Fields of papers citing papers by Andrew Howard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew Howard. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew Howard. The network helps show where Andrew Howard may publish in the future.

Co-authorship network of co-authors of Andrew Howard

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Howard. A scholar is included among the top collaborators of Andrew Howard based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew Howard. Andrew Howard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

#	Work	Indexed citations
1	A community driven, modular data-pipeline architecture to push EPRV into the 1 cm/s era 2024 ·Jennifer Burt, Chad F. Bender, Benjamin J. Fulton, Megan Bedell, C. A. Beichman, Lars A. Buchhave, (unknown), (unknown), Samuel Halverson, Andrew Howard, Marshall C. Johnson, (unknown), Sarah E. Logsdon, A. Quirrenbach, Andreas Seifahrt, Á. Szentgyörgyi, Lily Zhao	0
2	PikeLPN: Mitigating Overlooked Inefficiencies of Low-Precision Neural Networks 2024 ·(unknown), (unknown), (unknown), Chas Leichner, Shan Li, (unknown), Andrew Howard, Łukasz Lew, Sherief Reda, (unknown), (unknown)	1
3	BasisNet: Two-stage Model Synthesis for Efficient Inference 2021 ·Mingda Zhang, (unknown), Andrey Zhmoginov, Andrew Howard, Brendan Jou, Yukun Zhu, Li Zhang, Rebecca Hwa, Adriana Kovashka	1
4	Multi-path Neural Networks for On-device Multi-domain Visual Classification 2021 ·Qifei Wang, Junjie Ke, (unknown), Grace Chu, Gabriel Bender, Luciano Sbaiz, Alec Go, Andrew Howard, Ming–Hsuan Yang, (unknown), Peyman Milanfar, Feng Yang	3
5	Discovering Multi-Hardware Mobile Models via Architecture Search 2021 ·Grace Chu, Okan Arıkan, Gabriel Bender, Weijun Wang, (unknown), Pieter-Jan Kindermans, Hanxiao Liu, Berkin Akin, Suyog Gupta, Andrew Howard	7
6	The Public's Defender: Analyzing the Impact of Electing Public Defenders 2020 ·SSRN Electronic Journal ·Andrew Howard	1
7	Inverted Residuals and Linear Bottlenecks: Mobile Networks for Classification, Detection and Segmentation breakdown → 2018 ·arXiv (Cornell University) ·Andrew Howard, Andrey Zhmoginov, Liang-Chieh Chen, Mark Sandler, Menglong Zhu	386
8	K for the price of 1. Parameter efficient multi-task and transfer learning 2018 ·arXiv (Cornell University) ·(unknown), M. Sandler, Andrey Zhmoginov, Andrew Howard	7
9	Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning 2018 ·Yin Cui, Yang Song, Chen Sun, Andrew Howard, Serge Belongie	279
10	Effect of Accumulated Charge on the Total Ionizing Dose Response of a NAND Flash Memory 2012 ·IEEE Transactions on Nuclear Science ·Matthew Kay, Matthew J. Gadlage, Adam R. Duncan, (unknown), Andrew Howard, Timothy R. Oldham	20
11	Large margin transformation learning 2009 ·Tony Jebara, Andrew Howard	2
12	Transformation Learning Via Kernel Alignment 2009 ·Andrew Howard, Tony Jebara	5
13	Multi-object tracking with representations of the symmetric group. 2007 ·International Conference on Artificial Intelligence and Statistics ·Risi Kondor, Andrew Howard, Tony Jebara	37
14	Square Root Propagation 2005 ·Columbia Academic Commons (Columbia University) ·Andrew Howard, Tony Jebara	3
15	Dynamical systems trees 2004 ·Uncertainty in Artificial Intelligence ·Andrew Howard, Tony Jebara	14
16	Probability Product Kernels 2004 ·Journal of Machine Learning Research ·Tony Jebara, Risi Kondor, Andrew Howard	282

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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